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Microsoft Azure AI Fundamentals Certification | Exam AI-900

In just 1 day, achieve your Microsoft Azure AI Fundamentals Certification.


On this accelerated Microsoft Certified: Azure AI Fundamentals course, you’ll learn the fundamentals of artificial intelligence (AI) and how Microsoft Azure services can be used to design and establish AI solutions.

In just 1 day, you’ll build knowledge on:

  • The capabilities of no-code machine learning with Azure Machine Learning
  • Azure tools and services for NLP workloads
  • The features of common NLP Workload Scenarios

Choosing to get certified with Firebrand Sprint means you’ll get access to measure-ups, labs, and be given an exam voucher to sit Exam AI-900 and achieve your certification. As Firebrand are a Microsoft Gold Partner for Learning, you’ll also get access to the Microsoft Official Curriculum (MOCs) and learn from Microsoft Certified Trainers (MCTs).


Microsoft Azure AI Fundamentals: AI-900T00-AC

  • Module 1: Explore Fundamentals of Artificial Intelligence
  • Module 2: Explore Fundamentals of Machine Learning
  • Module 3: Explore Fundamentals of Computer Vision
  • Module 4: Explore Fundamentals of Natural Language Processing


If you’re interested in AI solutions and how Microsoft Azure services can be used to create them, this course is ideal for you.


Before attending this accelerated course, you should have:

  • Foundational knowledge of Machine Learning (ML)
  • Knowledge in Artificial Intelligence (AI) concepts
  • Knowledge of Microsoft Azure services

It would also be useful - but not necessary - to have general programming knowledge or experience.

Exam Track

As part of your accelerated course, you’ll sit the following exam covered by your Certification Guarantee:

Exam AI-900: Microsoft Azure AI Fundamentals

  • Exam code: AI-900
  • Languages: English
  • Domains:
    1. Describe Artificial Intelligence workloads and considerations (20-25%)
    2. Describe fundamental principles of machine learning on Azure (25-30%)
    3. Describe features of computer vision workloads on Azure (15-20%)
    4. Describe features of Natural Language Processing (NLP) workloads on Azure (25-30%)

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